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S&M3705 Research Paper of Special Issue https://doi.org/10.18494/SAM4885 Published: July 24, 2024 Implementation of Interactive System with Millimeter Wave and Wavelet Transform [PDF] Bo-Heng Chen, Da-Chuan Chen, Wen-Hsiang Yeh, Hao-Yang Chen, and Yu-Ping Liao (Received January 3, 2024; Accepted June 21, 2024) Keywords: deep neural network, object recognition, millimeter-wave radar, thermal imager, gesture recognition
In current society, escalating stress in everyday life and work creates significant concern about the potential for both physical and psychological long-term effects if unattended. To address this challenge, in this paper, we introduce a new approach designed to alleviate stress and promote well-being. Our proposed system synchronizes pointer swings with music rhythms to achieve a combination of rhythmic music engagement and interactive physical activity. This solution centers on the intersection of technology and well-being by providing users with an immersive and relaxing audio-visual experience. To achieve higher rhythm extraction precision in different genres of music, we employ wavelet transform and deep learning (DL) to adjust parameters dynamically. The controllable rotating sphere is achieved using a millimeter-wave (mmWave) radar and a thermographic camera to detect preset gestures. This system provides the interaction of rhythm and control over the rotating sphere, which can provide users with an immersive experience and contribute to a stress-relieving experience.
Corresponding author: Yu-Ping LiaoThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Bo-Heng Chen, Da-Chuan Chen, Wen-Hsiang Yeh, Hao-Yang Chen, and Yu-Ping Liao, Implementation of Interactive System with Millimeter Wave and Wavelet Transform, Sens. Mater., Vol. 36, No. 7, 2024, p. 2851-2866. |